US20060241376A1 - Non-invasive left ventricular volume determination - Google Patents

Non-invasive left ventricular volume determination Download PDF

Info

Publication number
US20060241376A1
US20060241376A1 US10/554,021 US55402105A US2006241376A1 US 20060241376 A1 US20060241376 A1 US 20060241376A1 US 55402105 A US55402105 A US 55402105A US 2006241376 A1 US2006241376 A1 US 2006241376A1
Authority
US
United States
Prior art keywords
endocardial
volume
contours
cardiac cycle
cardiac
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
US10/554,021
Other versions
US7603154B2 (en
Inventor
Nicholas Noble
Marcel Breeuwer
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Koninklijke Philips NV
Original Assignee
Koninklijke Philips Electronics NV
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Koninklijke Philips Electronics NV filed Critical Koninklijke Philips Electronics NV
Assigned to KONINKLIJKE PHILIPS ELECTRONICS, N.V. reassignment KONINKLIJKE PHILIPS ELECTRONICS, N.V. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: BREEUWER, MARCEL, NOBLE, NICHOLAS MICHAEL IAN
Publication of US20060241376A1 publication Critical patent/US20060241376A1/en
Application granted granted Critical
Publication of US7603154B2 publication Critical patent/US7603154B2/en
Active legal-status Critical Current
Adjusted expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/60Analysis of geometric attributes
    • G06T7/62Analysis of geometric attributes of area, perimeter, diameter or volume
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • G06T2207/30048Heart; Cardiac

Definitions

  • This invention pertains in general to the field of four dimensional image analyses and more particularly to the analysis of a cine sequence of captured cardiac images and even more particularly to left ventricular volume determination from a cine sequence of captured cardiac images.
  • Magnetic Resonance Imaging is more and more getting accepted as the golden standard for this volume assessment because of its superior spatio temporal and ‘anatomical’ resolution.
  • Magnetic (MRI) is an imaging technique used primarily in medical settings to produce high quality images of the inside of the human body.
  • MRI is based on the principles of nuclear magnetic resonance (NMR) and has advanced to a volume imaging technique. Slices having a defined slice thickness are composed of several volume elements or voxels. The volume of a voxel is calculated as the inplane resolution within the slice, e.g.
  • the magnetic resonance image is composed of several picture elements called pixels.
  • the intensity of a pixel is proportional to the NMR signal intensity of the contents of the corresponding volume element or voxel of the object being imaged.
  • a short-axis study of the heart consists of multiple slices covering a certain portion of the heart and multiple phases within the cardiac cycle.
  • the study is captured by means of a device for imaging inside parts of a mammal body, such as e.g. Magnetic Resonance (MR), Computer Tomography (CT), Ultrasound (US) or Nuclear Medicine (NM) devices.
  • MR Magnetic Resonance
  • CT Computer Tomography
  • US Ultrasound
  • NM Nuclear Medicine
  • a full cardiac contraction cycle i.e. one heartbeat from end-diastole (heart fully relaxed, ED) to end-systole (heart fully contracted, ES) and back to ED, is typically obtained at approximately 20 phases in the cardiac cycle.
  • the approach that is generally taken to measure the LV volume from MR images consists of two steps. First the endocardial contours, i.e. the inner myocardium boundaries, are delineated in all MR images of a MR cardiac study, usually short-axis slices.
  • the myocardium is the heart's muscular wall. It contracts to pump blood out of the heart, then relaxes as the heart refills with returning blood. Its outer surface is called the epicardium and its inner lining is called the endocardium.
  • the LV volume is calculated on the basis of the area within the contour and knowledge about the slice distance and thus the voxel volume.
  • Another method of determining LV volume is disclosed in U.S. Pat. No. -B1-6,438,403.
  • a seed voxel is within the image area of the LV chamber is identified and the intensity values of neighbouring voxels are compared to a threshold to determine whether the voxel corresponds to blood or muscle tissue.
  • For each neighbour voxel corresponding to blood its neighbour voxels are identified and compared to the threshold, whereby this process is repeated until a pre-established spatial boundary is encountered or the number of new neighbour voxels indicates that processing is migrating into an adjacent cardiac chamber.
  • the number of identified blood voxels is used for calculating ventricular volume. A large number of voxels has to be compared to neighbouring voxels.
  • One object of the invention is a reliable way of non-invasively determining LV volume during a cardiac cycle. Another object is to provide a method being less computational demanding than the prior art methods, so that results are faster available.
  • the present invention overcomes the above-identified deficiencies in the art and solves at least the above identified problems by providing a method and a computer readable medium comprising a computer program according to the appended patent claims.
  • the general solution according to the invention is to estimate LV volume using only endocardial contours in the 3D image that was acquired at end diastole (ED), i.e. the moment at which the heart is fully relaxed. These contours may be manually specified or (semi-)automatically derived. Based on these contours and on the pixel intensity in all other images, the LV volume is estimated.
  • ED end diastole
  • the image based LV volume determination method according to the invention is based on intensity variations within the cine series.
  • the theory behind this is based on the following:
  • the signal intensity of blood is approximately constant through out the cardiac cycle independently of the imaging method used for acquiring the images, such as e.g. MR, CT, US, NM.
  • the intensity of blood significantly differs from that of the myocardium; for CT and MR blood is brighter than the myocardial tissue and the blood intensity is very strong, much stronger than that of myocardium or lung tissue, and of comparable intensity to any epicardial fat that may be present.
  • CT and MR blood is brighter than the myocardial tissue and the blood intensity is very strong, much stronger than that of myocardium or lung tissue, and of comparable intensity to any epicardial fat that may be present.
  • US and NM blood is usually dark and the myocardial tissue is brighter.
  • there is a intensity contrast between myocardial tissue and blood independently from the imaging device/method used.
  • a method and a computer-readable medium for determining total left ventricular (LV) volume during a cardiac cycle from a by means of a device for imaging inside parts of a mammal body captured cine series of cardiac images are disclosed.
  • the device for imaging inside parts of a mammal body are a Magnetic Resonance (MR), Computer Tomography (CT) or Nuclear Medicine (NM) modality or a Ultrasound (US) Device.
  • MR Magnetic Resonance
  • CT Computer Tomography
  • NM Nuclear Medicine
  • US Ultrasound
  • a method determines total left ventricular (LV) volume during a cardiac cycle from a cardiac cine series.
  • the method comprises the steps of delineating endocardial and epicardial contours of a left ventricle in all slices of the cardiac cine series at end-diastole (ED) and subsequently applying these endocardial contours, which were delineated at ED, to all phases of the cardiac cycle, and calculating the total LV volume based on intensity values inside these endocardial contours delineated at ED.
  • a computer-readable medium having embodied thereon a computer program for processing by a computer for calculating total left ventricular (LV) volume during a cardiac cycle from a cardiac cine series.
  • the computer program comprises a first code segment for delineating endocardial and epicardial contours of a left ventricle in all slices of a cardiac cine series at end-diastole (ED), a second code segment for applying the endocardial contours delineated at ED to all phases of the cardiac cycle, and a third code segment for calculating the total LV volume based on intensity values inside the endocardial contours delineated at ED.
  • ED end-diastole
  • the present invention has the advantage over the prior art that it provides a reliable non-invasive fast evaluation of LV volume during cardiac cycles. Furthermore the determination of LV volume according to the invention is highly accurate and reproducible.
  • FIG. 1 is a perspective view schematically illustrating the term “short axis”
  • FIG. 2A is a cardiac MR image showing delineated endo- and epicardial walls of the LV myocardium in ED;
  • FIG. 2B is a schematic illustration of FIG. 2A ;
  • FIG. 3A is a cardiac MR image showing delineated endo- and epicardial walls of the LV myocardium in ES;
  • FIG. 3B is a schematic illustration of FIG. 3A ;
  • FIG. 4A is a cardiac MR sequence of 8 MR images during the cardiac cycle from ED to ES with delineations of the endocardial and epicardial wall of the LV myocardium derived at ED and copied to the subsequent phases;
  • FIG. 4B is a schematic illustration of FIG. 4A ;
  • FIG. 5 is a flow chart illustrating an embodiment of the method according to the invention.
  • FIGS. 6 and 7 are graphs illustrating the variation of total LV volume during a cardiac cycle calculated according to the method of the invention for two patients compared to manual delineated calculation of the whole sequence;
  • FIG. 8 is a set of graphs illustrating the variation of LV volume in different MR slices during a cardiac cycle calculated according to the method of the invention for six patients compared to manual delineated calculation of the whole sequence;
  • FIG. 9 is a schematic diagram illustrating an embodiment of the computer-readable medium according to the invention.
  • a method 10 is shown.
  • the LV volume is calculated over a cardiac cycle by evaluating a short-axis MRI cine series of the heart consisting of multiple slices covering the whole heart and multiple phases within the cardiac cycle.
  • the MRI cine series of the cardiac cycle is not limited to MRI cine series and the MRI cine series of the embodiment as described herein is not limiting.
  • the method according to the invention may determine LV volume from any cardiac cine series, independently from the method or device by means of which the cardiac cine series is captured.
  • the definition of a short-axis slice is illustrated in FIG. 1 , wherein a long axis 2 and a short-axis slice 3 are shown.
  • the schematic illustration of cardiac components 1 shows the left ventricle 6 , the right ventricle 7 , the myocardium 4 , the epicardium 8 and the endocardium 5 .
  • the first image in a MRI cine series corresponds to the ED phase in the cardiac cycle. This assumption is not true for all of the image sets that are used; the first image is however at most two images away from the ED phase.
  • the ED phase being defmed here as the phase at which the in-slice volume contained by a manually created endocardial contour is greatest.
  • a simple re-ordering of the images can be done so that it becomes the first image.
  • the blood volume at any subsequent phase in the cardiac cycle will be less than the blood volume at ED.
  • Manual observation of the heart shows a tendency for the epicardial contour, i.e. the outer boundaries of the myocardium, to stay relatively fixed throughout the cardiac cycle, and the endocardial surface to move inwards, approximately towards the centroid of the left ventricular blood pool, as it approaches ES. This can be seen in the exemplary image sequence shown in FIG. 4 .
  • Endocardial delineation performed at ED will thus contain the LV blood pool for all slices, when the ED endocardial delineation is copied onto all subsequent phases. It is also, due to the relatively stationary nature of the epicardial surface, unlikely to contain the epicardial surface, or any organs beyond that Such a delineation, copied to all subsequent phases will hence contain signals that originate solely from the LV myocardium and LV blood pool.
  • Any motion of the heart may automatically be compensated with (rigid) registration techniques such as motion compensation used for 1 st -pass myocardial perfusion MR image series, as e.g. described in M. Breeuwer, M. Quist, L. Spreeuwers, I. Paetsch, N. Al-Saadi and E. Nagel, “Towards automatic quantitative analysis of cardiac MR perfusion images”, Proceedings CARS 2001, June 2001, Berlin, Germany.
  • FIG. 3A is an exemplary MR image 300 ( FIG. 3A ) and a corresponding schematic illustration 301 is shown in FIG. 3B .
  • the endocardium delineation at ES is delineated with the line 31 indicated in FIGS. 3A and 3B .
  • the LV blood pool at ES is shown at 32 .
  • the epicardium delineation 30 at ES is approximately the same as the epicardium delineation 20 at ED.
  • FIGS. 4A and 4B illustrate a cine sequence from ED 41 to ES 42 over time t.
  • FIG. 4A is an exemplary MR cine sequence 400 and a corresponding schematic illustration 401 is shown in FIG. 4B .
  • Line 45 indicates the endocardium boundary at subsequent phases after ED and contains the blood pool 46 .
  • the dotted line 21 from ED to ES indicates the endocardium delineation made at ED.
  • n is the total number of slices comprising the LV total volume
  • V ED,i is the calculated volume of slice number i of the LV at end-diastole of the LV
  • I T,i is the detected intensity of slice i within the endocardial delimitation
  • IT is the total intensity at ED. This is performed in step 53 of the illustrated method.
  • V LV is a function of time t and varies during the cardiac cycle as described above (maximum at ED, minimum at ES). Two examples of calculated V LV (t) are shown as continuous lines in FIGS. 6 and 7 . Therefore it is checked in step 54 of the method, if the LV volume has been calculated for all phases of the examined cardiac cycle from the MR cine 20 . series. Until all LV volumes for all phases are calculated, the method branches back to step 53 , by increasing to the next phase slices in step 55 and calculating the intensities within the copied ED endocardial delineation as described above. In this way the LV volume for all slices is summed up to a total LV volume for each phase, fmally resulting in the total LV volume over the whole MR cine series as shown in the graphs in FIGS. 6 and 7 .
  • Short axis electrocardiogram triggered steady state free precession SENSE images were obtained in ten patients undergoing cardiac MRI for the investigation of coronary artery disease.
  • Three slices corresponding to approximately basal, mid and apical positions were selected from 8-9 contiguous slices, imaged with slice thickness 8-10 mm; field of view 350 ⁇ 344-390 ⁇ 390 mm; image size 256 ⁇ 256; 20-25 phases in the cardiac cycle; flip angle 50-55°; TE 1.56-1.68 ms; TR 3.11-3.37 ms.
  • the images were acquired on a Philips Gyrostan Intera 1.5 T with master gradients, using a five-element cardiac synergy coil, and vector electrocardiogram.
  • the graphs in FIGS. 6 to 8 show similar shape and features to the volumes produced by the manual delineations.
  • FIG. 9 shows a schematic diagram over another embodiment 9 of the invention.
  • a computer-readable medium 90 has embodied thereon a computer program for processing by a computer 91 for calculating total left ventricular (LV) volume during a cardiac cycle from a MRI cine series is provided.
  • the computer program comprises a first code segment 92 for delineating endocardial and epicardial contours of a left ventricle in all slices of a MR cine series at end-diastole (ED), a second code 93 segment for applying the endocardial contours delineated at ED to all phases of the cardiac cycle, and a third code segment 94 for calculating the total LV volume based on intensity values inside the endocardial contours delineated at ED.
  • the computer is generally a general purpose computer.
  • SSFP MR images are especially well suited for the LV volume determination according to the invention because the signal intensity of blood in SSFP MR images is approximately constant through out the cardiac cycle.
  • the method can also be used as a first step in the temporal registration of LV functional images acquired at different stress levels.
  • LV function is usually assessed at a number of (pharmacologically induced) stress levels (4-5 levels).
  • the temporal behaviour of the heart as a function of increasing stress is highly non-linear, which means that the resulting phases cannot simply be matched by linear scaling of the temporal axis.
  • the temporal scaling may be performed using the measured LV volume curves as one of the inputs. In these curves, the contraction and relaxation intervals may for example be determined and these intervals may be matched between the stress levels.
  • CMR functional cardiac MR
  • phase information there are several manners in which one could derive such phase information, the two principle manners from which one might determine the phase are, from a simultaneously recorded ECG signal, or from the actual image data.
  • the determination of phase in the cardiac cycle is performed via analysis of the MRI cine image series.
  • the most obvious and most frequently used image derived method of determining phase is via manual observation of the cine series.
  • an analysis of the volume contained by delineations of the left ventricular endocardial surface can be performed. This has been used to identify end-diastole and end-systole in the commercially available MASS package (Version 4.2, Medis, Leiden, the Netherlands).
  • MASS package Version 4.2, Medis, Leiden, the Netherlands.
  • the ED and ES phases are identified, where a representation of the entire cardiac cycle is required, linear interpolation between these points has been performed.
  • a set of endocardial delineations, whether manually, or automatically produced contain sufficient data to perform a detailed analysis of the phase in the cardiac cycle.
  • automatic delineation techniques encounter difficulties when delineating as described above.
  • an pre-processing step is to invert the images before applying the LV volume measurement method according to the invention.
  • the method according to the invention is generally implemented on a general purpose computer. However, the method may also be implemented in dedicated solutions, such as code segments for execution by e.g. a DSP chip, a specifically designed integrated circuit such as an ASIC, etc.

Abstract

A method of and a computer readable medium comprising a program for calculating total left ventricular (LV) volume during a cardiac cycle. The LV volume is estimated using only endocardial contours in a cardiac 3D image that was acquired at end diastole (ED), i.e. the moment at which the heart is fully relaxed. These contours are manually specified or (semi-)automatically derived. Based on these contours and on the pixel intensity in all other images, the LV volume is estimated based on intensity variations within the area enclosed by the contours (ED LV blood pool). These variations are proportional to the change in size of the ventricle. Hence ventricle volume and other derivable cardiac functionality parameters as well as the phase in the cardiac cycle are derived. The 3D image is previously to the method captured by means of a device for imaging inside parts of a mammal body, such as Magnetic Resonance (MR), Computer Tomography (CT), Nuclear Medicine (NM) or Ultrasound (US) devices.

Description

  • This invention pertains in general to the field of four dimensional image analyses and more particularly to the analysis of a cine sequence of captured cardiac images and even more particularly to left ventricular volume determination from a cine sequence of captured cardiac images.
  • The assessment of the blood volume of the left ventricle (LV) of the heart as a function of time is of importance for the evaluation of the pump function of the heart. Magnetic Resonance Imaging (MRI) is more and more getting accepted as the golden standard for this volume assessment because of its superior spatio temporal and ‘anatomical’ resolution. Magnetic (MRI) is an imaging technique used primarily in medical settings to produce high quality images of the inside of the human body. MRI is based on the principles of nuclear magnetic resonance (NMR) and has advanced to a volume imaging technique. Slices having a defined slice thickness are composed of several volume elements or voxels. The volume of a voxel is calculated as the inplane resolution within the slice, e.g. 3 mm2, multiplied with the through-plane resolution, i.e. the slice distance, e.g. 3 mm, which results in a voxel volume of 3mm3 for the given example. The magnetic resonance image is composed of several picture elements called pixels. The intensity of a pixel is proportional to the NMR signal intensity of the contents of the corresponding volume element or voxel of the object being imaged.
  • A short-axis study of the heart consists of multiple slices covering a certain portion of the heart and multiple phases within the cardiac cycle. The study is captured by means of a device for imaging inside parts of a mammal body, such as e.g. Magnetic Resonance (MR), Computer Tomography (CT), Ultrasound (US) or Nuclear Medicine (NM) devices. The sequence of images is available for further analysis.
  • For the assessment of LV volume the left and right ventricle are covered from apex (bottom) to base (valvular plane) in such a study. Thus four-dimensional images of the heart are available. Multiple slices (approximately 10 to 15) compose a three dimensional image of the heart. The fourth dimension is time. A full cardiac contraction cycle, i.e. one heartbeat from end-diastole (heart fully relaxed, ED) to end-systole (heart fully contracted, ES) and back to ED, is typically obtained at approximately 20 phases in the cardiac cycle.
  • The approach that is generally taken to measure the LV volume from MR images consists of two steps. First the endocardial contours, i.e. the inner myocardium boundaries, are delineated in all MR images of a MR cardiac study, usually short-axis slices. The myocardium is the heart's muscular wall. It contracts to pump blood out of the heart, then relaxes as the heart refills with returning blood. Its outer surface is called the epicardium and its inner lining is called the endocardium. Thereafter the LV volume is calculated on the basis of the area within the contour and knowledge about the slice distance and thus the voxel volume.
  • Several methods for automatic delineation of the LV endocardial contours have been proposed. However, so far none of these can perform a true automatic delineation, since the clinical user has to perform a significant number of manual contour corrections. In the presence of papiliary muscles and trabeculae, at apical positions in the myocardium or when delineating the ES phase, spurious results are produced by the methods according to the prior art. The vast amount of clinician time is required to perform a set of delineations on a typical MRI cine series, i.e. approximately 400 delineations per series or several hours of manual work. For instance 20 phases times 10 slices times 2 contours=400 contours times 10 sec per contour=1 hour and 11 minutes; in reality however this may have to be done for 4-5 stress levels, so the total time can be up to 5 hours. This time constraint is prohibitive to the routine incorporation of manual delineation in LV volume determination.
  • Another method of determining LV volume is disclosed in U.S. Pat. No. -B1-6,438,403. A seed voxel is within the image area of the LV chamber is identified and the intensity values of neighbouring voxels are compared to a threshold to determine whether the voxel corresponds to blood or muscle tissue. For each neighbour voxel corresponding to blood, its neighbour voxels are identified and compared to the threshold, whereby this process is repeated until a pre-established spatial boundary is encountered or the number of new neighbour voxels indicates that processing is migrating into an adjacent cardiac chamber. The number of identified blood voxels is used for calculating ventricular volume. A large number of voxels has to be compared to neighbouring voxels. This method is complicated and demanding with regard to computational power. Depending on the power of the computer equipment used to perform the calculations, it takes either a long time to get a calculated result or if fast equipment is used, this means that it is expensive in terms of money to carry out the calculation. Another drawback of this method is the fact that a seed voxel has to be identified either manually or automatically, which in both cases is prone to errors. Furthermore the method of seeded region growing has the general disadvantage that it can only detect the volume in which the seed is positioned. If, for example, due to the specific geometry of the papillary muscles the LV volume consists of two non-connected subvolumes one of the two may be missed and the LV volume calculated according to the method of U.S. Pat. No. -B1-6,438,403 is not correct.
  • One object of the invention is a reliable way of non-invasively determining LV volume during a cardiac cycle. Another object is to provide a method being less computational demanding than the prior art methods, so that results are faster available.
  • The present invention overcomes the above-identified deficiencies in the art and solves at least the above identified problems by providing a method and a computer readable medium comprising a computer program according to the appended patent claims.
  • The general solution according to the invention is to estimate LV volume using only endocardial contours in the 3D image that was acquired at end diastole (ED), i.e. the moment at which the heart is fully relaxed. These contours may be manually specified or (semi-)automatically derived. Based on these contours and on the pixel intensity in all other images, the LV volume is estimated.
  • More particularly, the image based LV volume determination method according to the invention is based on intensity variations within the cine series. The theory behind this is based on the following:
  • The signal intensity of blood is approximately constant through out the cardiac cycle independently of the imaging method used for acquiring the images, such as e.g. MR, CT, US, NM.
  • The intensity of blood significantly differs from that of the myocardium; for CT and MR blood is brighter than the myocardial tissue and the blood intensity is very strong, much stronger than that of myocardium or lung tissue, and of comparable intensity to any epicardial fat that may be present. In US and NM blood is usually dark and the myocardial tissue is brighter. Thus there is a intensity contrast between myocardial tissue and blood, independently from the imaging device/method used.
  • Changes in the histogram across the cardiac cycle are dominated by the strong signal coming from the blood in the ventricles as they change size.
  • This change is proportional to the change in size of the ventricles, this measure provides hence a way for determining the ventricle volume and other derivable cardiac functionality parameters as well as the phase in the cardiac cycle.
  • According to aspects of the invention, a method and a computer-readable medium for determining total left ventricular (LV) volume during a cardiac cycle from a by means of a device for imaging inside parts of a mammal body captured cine series of cardiac images are disclosed. Preferably the device for imaging inside parts of a mammal body are a Magnetic Resonance (MR), Computer Tomography (CT) or Nuclear Medicine (NM) modality or a Ultrasound (US) Device.
  • According to one aspect of the invention, a method is provided, wherein the method determines total left ventricular (LV) volume during a cardiac cycle from a cardiac cine series. The method comprises the steps of delineating endocardial and epicardial contours of a left ventricle in all slices of the cardiac cine series at end-diastole (ED) and subsequently applying these endocardial contours, which were delineated at ED, to all phases of the cardiac cycle, and calculating the total LV volume based on intensity values inside these endocardial contours delineated at ED.
  • According to another aspect of the invention, a computer-readable medium having embodied thereon a computer program for processing by a computer for calculating total left ventricular (LV) volume during a cardiac cycle from a cardiac cine series is provided. The computer program comprises a first code segment for delineating endocardial and epicardial contours of a left ventricle in all slices of a cardiac cine series at end-diastole (ED), a second code segment for applying the endocardial contours delineated at ED to all phases of the cardiac cycle, and a third code segment for calculating the total LV volume based on intensity values inside the endocardial contours delineated at ED.
  • The present invention has the advantage over the prior art that it provides a reliable non-invasive fast evaluation of LV volume during cardiac cycles. Furthermore the determination of LV volume according to the invention is highly accurate and reproducible.
  • Further objects, features and advantages of the invention will become apparent from the following description of embodiments of the present invention, reference being made to the accompanying drawings, in which
  • FIG. 1 is a perspective view schematically illustrating the term “short axis”;
  • FIG. 2A is a cardiac MR image showing delineated endo- and epicardial walls of the LV myocardium in ED;
  • FIG. 2B is a schematic illustration of FIG. 2A;
  • FIG. 3A is a cardiac MR image showing delineated endo- and epicardial walls of the LV myocardium in ES;
  • FIG. 3B is a schematic illustration of FIG. 3A;
  • FIG. 4A is a cardiac MR sequence of 8 MR images during the cardiac cycle from ED to ES with delineations of the endocardial and epicardial wall of the LV myocardium derived at ED and copied to the subsequent phases;
  • FIG. 4B is a schematic illustration of FIG. 4A;
  • FIG. 5 is a flow chart illustrating an embodiment of the method according to the invention;
  • FIGS. 6 and 7 are graphs illustrating the variation of total LV volume during a cardiac cycle calculated according to the method of the invention for two patients compared to manual delineated calculation of the whole sequence;
  • FIG. 8 is a set of graphs illustrating the variation of LV volume in different MR slices during a cardiac cycle calculated according to the method of the invention for six patients compared to manual delineated calculation of the whole sequence; and
  • FIG. 9 is a schematic diagram illustrating an embodiment of the computer-readable medium according to the invention.
  • In an embodiment of the invention according to FIG. 5, a method 10 is shown. According to the method 10, the LV volume is calculated over a cardiac cycle by evaluating a short-axis MRI cine series of the heart consisting of multiple slices covering the whole heart and multiple phases within the cardiac cycle. The MRI cine series of the cardiac cycle is not limited to MRI cine series and the MRI cine series of the embodiment as described herein is not limiting. Moreover the method according to the invention may determine LV volume from any cardiac cine series, independently from the method or device by means of which the cardiac cine series is captured. The definition of a short-axis slice is illustrated in FIG. 1, wherein a long axis 2 and a short-axis slice 3 are shown. Furthermore the schematic illustration of cardiac components 1 shows the left ventricle 6, the right ventricle 7, the myocardium 4, the epicardium 8 and the endocardium 5.
  • It is assumed in the method that the first image in a MRI cine series corresponds to the ED phase in the cardiac cycle. This assumption is not true for all of the image sets that are used; the first image is however at most two images away from the ED phase. The ED phase being defmed here as the phase at which the in-slice volume contained by a manually created endocardial contour is greatest. In case the ED image is at another position of the cine sequence, a simple re-ordering of the images can be done so that it becomes the first image.
  • Following this assumption, the blood volume at any subsequent phase in the cardiac cycle will be less than the blood volume at ED. Manual observation of the heart shows a tendency for the epicardial contour, i.e. the outer boundaries of the myocardium, to stay relatively fixed throughout the cardiac cycle, and the endocardial surface to move inwards, approximately towards the centroid of the left ventricular blood pool, as it approaches ES. This can be seen in the exemplary image sequence shown in FIG. 4.
  • Endocardial delineation performed at ED will thus contain the LV blood pool for all slices, when the ED endocardial delineation is copied onto all subsequent phases. It is also, due to the relatively stationary nature of the epicardial surface, unlikely to contain the epicardial surface, or any organs beyond that Such a delineation, copied to all subsequent phases will hence contain signals that originate solely from the LV myocardium and LV blood pool. Any motion of the heart may automatically be compensated with (rigid) registration techniques such as motion compensation used for 1st-pass myocardial perfusion MR image series, as e.g. described in M. Breeuwer, M. Quist, L. Spreeuwers, I. Paetsch, N. Al-Saadi and E. Nagel, “Towards automatic quantitative analysis of cardiac MR perfusion images”, Proceedings CARS 2001, June 2001, Berlin, Germany.
  • By means of endocardial delineation 21 and epicardial delineation 20 for the first image in the cine series (approximately ED) the mean voxel intensity of myocardium 23 (between delineations 20,21) is calculated. This is shown in FIGS. 2A and 2B in an exemplary MR image 200 (FIG. 2A) and a corresponding schematic illustration 201 (FIG. 2B) with the LV blood volume 22 inside the endocardial delineation 21. When the endocardial delineation 21 is copied and pasted to subsequent phases (as shown in FIGS. 4a and 4B) and the contained voxels are integrated, the integral is principally due to the intensities of the blood and the myocardium contained, that is:
    I T =I B =+I MYO (1)
  • Where IT is the total signal intensity, IB the signal intensity due to the blood and IMYO the signal intensity due to any myocardium that is contained by the contour. As can be seen in FIGS. 3A, 3B and FIGS. 4A, 4B the endocardium moves towards the centroid of the LV blood volume. FIG. 3A is an exemplary MR image 300 (FIG. 3A) and a corresponding schematic illustration 301 is shown in FIG. 3B. The endocardium delineation at ES is delineated with the line 31 indicated in FIGS. 3A and 3B. The LV blood pool at ES is shown at 32. The epicardium delineation 30 at ES is approximately the same as the epicardium delineation 20 at ED. Thus the contribution of the myocardium to the total intensity will increase from ED (image 41 in FIG. 4A) to ES (image 42 in FIG. 4A) and decrease from ES back to ED. Other contributions may arise from the lung, the right ventricular blood pool and epicardial fat. These will only occur if the heart moves sufficiently for these to be covered by the endocardial contour at subsequent phases.
  • FIGS. 4A and 4B illustrate a cine sequence from ED 41 to ES 42 over time t. FIG. 4A is an exemplary MR cine sequence 400 and a corresponding schematic illustration 401 is shown in FIG. 4B. Line 45 indicates the endocardium boundary at subsequent phases after ED and contains the blood pool 46. The dotted line 21 from ED to ES indicates the endocardium delineation made at ED.
  • The total area contained by the contour (AT), is equal to the sum of the areas due to the blood (AB) and the myocardium (AMYO), such that:
    A T =A B +A Myo (2)
  • These areas are calculated in step 51.
  • Calculating the mean intensity per voxel, for both myocardium (SMYO) and blood (SB), is performed in step 52 of the method, wherein both are calculated from the initial endocardial and epicardial delineations, and assuming that the signal intensity is proportional to the area contained, it is:
    I B =A B ×S B (3)
    and
    I MYO =A MYO ×S MYO (4)
  • Solving equations 1, 2, 3 and 4 for the signal intensity due to the blood IB (equation 5), gives an improved estimate for the integral intensity due to blood. This includes compensation for signal originating from any myocardium that may be present. I B = S B I T - S B S MYO A T S B - S MYO ( 5 )
  • The total LV volume VLV filled with blood in a certain phase of a CMR cardiac cycle is thus calculated as: V LV = i = 1 n V ED , i I T , i I T , ED ( 6 )
  • wherein n is the total number of slices comprising the LV total volume, VED,i is the calculated volume of slice number i of the LV at end-diastole of the LV, IT,i is the detected intensity of slice i within the endocardial delimitation and IT, ED is the total intensity at ED. This is performed in step 53 of the illustrated method.
  • VLV is a function of time t and varies during the cardiac cycle as described above (maximum at ED, minimum at ES). Two examples of calculated VLV (t) are shown as continuous lines in FIGS. 6 and 7. Therefore it is checked in step 54 of the method, if the LV volume has been calculated for all phases of the examined cardiac cycle from the MR cine 20. series. Until all LV volumes for all phases are calculated, the method branches back to step 53, by increasing to the next phase slices in step 55 and calculating the intensities within the copied ED endocardial delineation as described above. In this way the LV volume for all slices is summed up to a total LV volume for each phase, fmally resulting in the total LV volume over the whole MR cine series as shown in the graphs in FIGS. 6 and 7.
  • Clinical studies were performed to validate the method. Short axis electrocardiogram triggered steady state free precession SENSE images were obtained in ten patients undergoing cardiac MRI for the investigation of coronary artery disease. Three slices corresponding to approximately basal, mid and apical positions were selected from 8-9 contiguous slices, imaged with slice thickness 8-10 mm; field of view 350×344-390×390 mm; image size 256×256; 20-25 phases in the cardiac cycle; flip angle 50-55°; TE 1.56-1.68 ms; TR 3.11-3.37 ms. The images were acquired on a Philips Gyrostan Intera 1.5 T with master gradients, using a five-element cardiac synergy coil, and vector electrocardiogram.
  • For each selected slice, of each image set, both endocardial and epicardial delineations were manually performed on the first image. From these delineations, AT, SMYO and SB were calculated. For each subsequent image, IT was calculated by summing the intensity values of all of the voxels contained by the endocardial delineation. IB was then calculated according to equation 5.
  • In order to verify the results, manual delineation was performed for every image and the number of voxels contained by that contour calculated. The number of voxels was multiplied by the volume of a single voxel to get a total endocardial volume for each image. The values of IB were normalised to the endocardial volume in order for them to be plotted on the same axes, by calculating the factor that forces the integral value for the first image to coincide with the volume contained by the manual delineation for that image. This factor was then applied to the intensity sums of all of the images of that slice. Graphs of the values produced can be seen in FIG. 8. These traces, follow their manually derived counterparts very well. The smooth nature of the intensity derived traces suggest a more plausible description of cardiac function than the ragged manually derived traces, which is due to the inherent error present in manual delineations.
  • The graphs in FIGS. 6 to 8 show similar shape and features to the volumes produced by the manual delineations.
  • Further improvements to this method, or at least to the results, may incorporate a delineation of papiliary muscles and allow for their subsequent affect on volume measurements. It is anticipated that such a modification would serve to further improve the similarity of the graphs obtained.
  • FIG. 9 shows a schematic diagram over another embodiment 9 of the invention. A computer-readable medium 90 has embodied thereon a computer program for processing by a computer 91 for calculating total left ventricular (LV) volume during a cardiac cycle from a MRI cine series is provided. The computer program comprises a first code segment 92 for delineating endocardial and epicardial contours of a left ventricle in all slices of a MR cine series at end-diastole (ED), a second code 93 segment for applying the endocardial contours delineated at ED to all phases of the cardiac cycle, and a third code segment 94 for calculating the total LV volume based on intensity values inside the endocardial contours delineated at ED. The computer is generally a general purpose computer.
  • When using MR images, Steady State Free Precession (SSFP) MR images are especially well suited for the LV volume determination according to the invention because the signal intensity of blood in SSFP MR images is approximately constant through out the cardiac cycle.
  • Apart from the assessment of the LV volume, the method can also be used as a first step in the temporal registration of LV functional images acquired at different stress levels. LV function is usually assessed at a number of (pharmacologically induced) stress levels (4-5 levels). The temporal behaviour of the heart as a function of increasing stress is highly non-linear, which means that the resulting phases cannot simply be matched by linear scaling of the temporal axis. The temporal scaling may be performed using the measured LV volume curves as one of the inputs. In these curves, the contraction and relaxation intervals may for example be determined and these intervals may be matched between the stress levels.
  • By means of the above described processing of functional cardiac MR (CMR) images, it is possible to determine at what point in the cardiac cycle a certain image was taken. These include: the determination of equivalent images in rest/stress data sets, the identification of ES for the optimisation of registration strategies or the assessment of tachycardia patients.
  • There are several manners in which one could derive such phase information, the two principle manners from which one might determine the phase are, from a simultaneously recorded ECG signal, or from the actual image data. An alternative, although extremely invasive method, would be via an analysis of the measurements taken by an intra-ventricular pressure catheter. According to an embodiment of the invention, the determination of phase in the cardiac cycle is performed via analysis of the MRI cine image series.
  • The most obvious and most frequently used image derived method of determining phase, is via manual observation of the cine series. Alternatively, an analysis of the volume contained by delineations of the left ventricular endocardial surface can be performed. This has been used to identify end-diastole and end-systole in the commercially available MASS package (Version 4.2, Medis, Leiden, the Netherlands). However, although the ED and ES phases are identified, where a representation of the entire cardiac cycle is required, linear interpolation between these points has been performed.
  • A set of endocardial delineations, whether manually, or automatically produced contain sufficient data to perform a detailed analysis of the phase in the cardiac cycle. Currently, automatic delineation techniques encounter difficulties when delineating as described above.
  • For those imaging modalities that show the myocardium brighter than the left ventricular blood pool an pre-processing step is to invert the images before applying the LV volume measurement method according to the invention.
  • The method according to the invention is generally implemented on a general purpose computer. However, the method may also be implemented in dedicated solutions, such as code segments for execution by e.g. a DSP chip, a specifically designed integrated circuit such as an ASIC, etc.
  • The present invention has been described above with reference to specific embodiments. However, other embodiments than the preferred above are equally possible within the scope of the appended claims, e.g. different ways of delineating the endocardial and epicardial contours than those described above, different ways of capturing the cine series, different ways of calculating intensities in the cine images, different slice thickness of the cine images, different number of phases/images representing the cardiac cycle, performing the above method by hardware or software, other image capturing devices or methods for acquiring the cardiac cine series, etc.
  • Furthermore, the term “comprises/comprising” when used in this specification does not exclude other elements or steps, the terms “a” and “an” do not exclude a plurality and a single processor or other units may fulfil the functions of several of the units or circuits recited in the claims.

Claims (12)

1. A method of determining total left ventricular (LV) interior volume during a cardiac cycle from a cardiac cine series, said method comprising the steps of:
delineating endocardial and epicardial contours of a left ventricle in all slices of said cine series at end-diastole (ED),
applying the endocardial contours delineated at ED to all phases of the cardiac cycle, and
calculating the total LV interior volume based on intensity values inside the endocardial contours delineated at ED.
2. The method according to claim 1, further comprising calculating a mean intensity for myocardium and blood voxels at ED based on the delineated endocardial and epicardial contours.
3. The method according to claim 2, further comprising using the mean intensities for compensating for myocardium enclosed in the endocardial contours delineated at ED during subsequent phases of the cardiac cycle.
4. The method according to claim 3, wherein the LV interior volume is calculated as
V LV = i = 1 n V ED , i I T , i I T , ED ,
wherein
n is the total number of slices comprising the LV total interior volume,
VED,i is the calculated interior volume of slice number i of the LV at end-diastole of the LV,
IT,i is the detected intensity of slice i within the endocardial delimitation, and
IT, ED is the total intensity at ED.
5. The method according to claim 1, wherein the cine series is a short-axis study of the heart consisting of multiple slices covering at least the left ventricle and multiple phases within the cardiac cycle.
6. The method according to claim 1, further comprising determining the LV volume from cine sequences acquired at different stress levels, whereby the temporal behaviour of the heart as a function of increasing stress is determined.
7. The method according to claim 1, wherein said cine series is/are captured previously to said method on a device for imaging inside parts of a mammal body.
8. The method according to claim 7, wherein said device for imaging inside parts of a mammal body is a Magnetic Resonance (MR), Computer Tomography (CT), Nuclear Medicine (NM) or Ultrasound (US) device.
9. The method according to claim 8, wherein an MRI study comprises Steady State Free Precession (SSFP) images.
10. The method according to claim 1, further comprising compensating motion of the heart.
11. A computer-readable medium (90) having embodied thereon a computer program for processing by a computer (91) for calculating total left ventricular (LV) volume during a cardiac cycle from a cine series, the computer program comprising:
a first code segment (92) for delineating endocardial and epicardial contours of a left ventricle in all slices of said cine series at end-diastole (ED),
a second code (93) segment for applying the endocardial contours delineated at ED to all phases of the cardiac cycle, and
a third code segment (94) for calculating the total LV volume based on intensity values inside the endocardial contours delineated at ED.
12. The computer-readable medium according to claim 11, wherein said first code segment automatically delineates the endocardial and epicardial contours.
US10/554,021 2003-04-24 2004-04-23 Non-invasive left ventricular volume determination Active 2024-07-17 US7603154B2 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
EP03101141 2003-04-24
EP03101141.4 2003-04-24
PCT/IB2004/050503 WO2004097720A1 (en) 2003-04-24 2004-04-23 Non-invasive left ventricular volume determination

Publications (2)

Publication Number Publication Date
US20060241376A1 true US20060241376A1 (en) 2006-10-26
US7603154B2 US7603154B2 (en) 2009-10-13

Family

ID=33395933

Family Applications (1)

Application Number Title Priority Date Filing Date
US10/554,021 Active 2024-07-17 US7603154B2 (en) 2003-04-24 2004-04-23 Non-invasive left ventricular volume determination

Country Status (7)

Country Link
US (1) US7603154B2 (en)
EP (1) EP1620827B1 (en)
JP (1) JP2006524092A (en)
CN (1) CN100377165C (en)
AT (1) ATE470199T1 (en)
DE (1) DE602004027479D1 (en)
WO (1) WO2004097720A1 (en)

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070253609A1 (en) * 2006-04-28 2007-11-01 Aben Jean-Paul M M Method, Apparatus and Computer Program Product for Automatic Segmenting of Cardiac Chambers
US20090149734A1 (en) * 2007-12-07 2009-06-11 Kabushiki Kaisha Toshiba Diagnostic imaging apparatus, magnetic resonance imaging apparatus, and x-ray ct apparatus
US20100303328A1 (en) * 2008-01-31 2010-12-02 Koninklijke Philips Electronics N.V. Automatic 3-d segmentation of the short-axis late-enhancement cardiac mri
WO2011107528A1 (en) 2010-03-04 2011-09-09 Europejskie Centrum Zdrowia Otwock Sp. Z O.O. A device and a method for imaging the left ventricle of a heart
US20120146632A1 (en) * 2009-07-20 2012-06-14 Koninklijke Philips Electronics N.V. Apparatus and method for influencing and/or detecting magnetic particles
US20140005526A1 (en) * 2012-07-02 2014-01-02 Assaf Govari Catheter with synthetic aperture mri sensor
US20150023577A1 (en) * 2012-03-05 2015-01-22 Hong'en (Hangzhou, China) Medical Technology Inc. Device and method for determining physiological parameters based on 3d medical images
WO2018140596A3 (en) * 2017-01-27 2018-09-07 Arterys Inc. Automated segmentation utilizing fully convolutional networks
US10398344B2 (en) 2014-01-17 2019-09-03 Arterys Inc. Apparatus, methods and articles for four dimensional (4D) flow magnetic resonance imaging
US10495713B2 (en) 2011-07-07 2019-12-03 The Board Of Trustees Of The Leland Stanford Junior University Comprehensive cardiovascular analysis with volumetric phase-contrast MRI
US10871536B2 (en) 2015-11-29 2020-12-22 Arterys Inc. Automated cardiac volume segmentation
US11515032B2 (en) 2014-01-17 2022-11-29 Arterys Inc. Medical imaging and efficient sharing of medical imaging information
US11551353B2 (en) 2017-11-22 2023-01-10 Arterys Inc. Content based image retrieval for lesion analysis

Families Citing this family (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006524092A (en) 2003-04-24 2006-10-26 コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ Non-invasive left ventricular volume determination
WO2005076186A1 (en) 2004-02-09 2005-08-18 Institut De Cardiologie De Montreal Computation of a geometric parameter of a cardiac chamber from a cardiac tomography data set
JP4679141B2 (en) * 2004-12-27 2011-04-27 株式会社東芝 Ultrasonic diagnostic apparatus and method for displaying ultrasonic diagnostic image
DE102006026695A1 (en) 2006-06-08 2007-12-13 Tomtec Imaging Systems Gmbh Method, apparatus and computer program product for evaluating dynamic images of a cavity
JP5751738B2 (en) * 2007-12-07 2015-07-22 株式会社東芝 Magnetic resonance imaging system
US8218839B2 (en) * 2008-05-23 2012-07-10 Siemens Aktiengesellschaft Automatic localization of the left ventricle in cardiac cine magnetic resonance imaging
US8331638B2 (en) * 2008-10-10 2012-12-11 Siemens Corporation Creation of motion compensated MRI M-mode images of the myocardial wall
US10078893B2 (en) 2010-12-29 2018-09-18 Dia Imaging Analysis Ltd Automatic left ventricular function evaluation
EP2765916B1 (en) 2011-10-12 2019-02-13 The Johns Hopkins University System for evaluating regional cardiac function and dyssynchrony from a dynamic imaging modality using endocardial motion
US9734430B2 (en) 2012-01-02 2017-08-15 Mackay Memorial Hospital Evaluation system or determination of cardiovascular function parameters
JP6238672B2 (en) * 2012-10-04 2017-11-29 東芝メディカルシステムズ株式会社 Ultrasonic diagnostic equipment
CN102961161A (en) * 2012-11-27 2013-03-13 华南理工大学 Method for automatically obtaining heart function parameters of four-dimensional heart
KR101616029B1 (en) 2014-07-25 2016-04-27 삼성전자주식회사 Magnetic resonance imaging processing method and apparatus thereof
KR101652046B1 (en) * 2014-11-03 2016-08-29 삼성전자주식회사 Medical imaging apparatus and processing method thereof
US10674986B2 (en) 2016-05-13 2020-06-09 General Electric Company Methods for personalizing blood flow models
CN108882917A (en) * 2016-05-30 2018-11-23 深圳迈瑞生物医疗电子股份有限公司 A kind of heart volume discriminance analysis system and method
PT3537977T (en) * 2016-11-11 2023-08-23 Medtrace Pharma As Method and system for modelling a human heart and atria
US10388015B2 (en) 2017-09-06 2019-08-20 International Business Machines Corporation Automated septal defect detection in cardiac computed tomography images
CN108703770B (en) * 2018-04-08 2021-10-01 智谷医疗科技(广州)有限公司 Ventricular volume monitoring device and method
CN112656445B (en) * 2020-12-18 2023-04-07 青岛海信医疗设备股份有限公司 Ultrasonic device, ultrasonic image processing method and storage medium

Citations (68)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5107838A (en) * 1990-02-08 1992-04-28 Kabushiki Kaisha Toshiba Method of left ventricular volume evaluation using nuclear magnetic resonance imaging
US5185809A (en) * 1987-08-14 1993-02-09 The General Hospital Corporation Morphometric analysis of anatomical tomographic data
US5195521A (en) * 1990-11-09 1993-03-23 Hewlett-Packard Company Tissue measurements
US5433199A (en) * 1994-02-24 1995-07-18 General Electric Company Cardiac functional analysis method using gradient image segmentation
US5435310A (en) * 1993-06-23 1995-07-25 University Of Washington Determining cardiac wall thickness and motion by imaging and three-dimensional modeling
US5722405A (en) * 1993-04-15 1998-03-03 Adac Laboratories Method and apparatus for acquisition and processsing of event data in semi list mode
US5797396A (en) * 1995-06-07 1998-08-25 University Of Florida Research Foundation Automated method for digital image quantitation
US6121775A (en) * 1998-06-16 2000-09-19 Beth Israel Deaconess Medical Center, Inc. MRI imaging method and apparatus
US6261549B1 (en) * 1997-07-03 2001-07-17 Osiris Therapeutics, Inc. Human mesenchymal stem cells from peripheral blood
US6288539B1 (en) * 1998-09-10 2001-09-11 Pheno Imaging, Inc. System for measuring an embryo, reproductive organs, and tissue in an animal
US6387367B1 (en) * 1998-05-29 2002-05-14 Osiris Therapeutics, Inc. Human mesenchymal stem cells
US20020072670A1 (en) * 2000-12-07 2002-06-13 Cedric Chenal Acquisition, analysis and display of ultrasonic diagnostic cardiac images
US20020072674A1 (en) * 2000-12-07 2002-06-13 Criton Aline Laure Strain rate analysis in ultrasonic diagnostic images
US6438403B1 (en) * 1999-11-01 2002-08-20 General Electric Company Method and apparatus for cardiac analysis using four-dimensional connectivity
US20020151793A1 (en) * 1998-08-25 2002-10-17 Geiser Edward A. Autonomous boundary detection system for echocardiographic images
US20030053667A1 (en) * 2001-05-17 2003-03-20 Nikolaos Paragios Variational approach for the segmentation of the left ventricle in MR cardiac images
US20030069494A1 (en) * 2001-10-04 2003-04-10 Marie-Pierre Jolly System and method for segmenting the left ventricle in a cardiac MR image
US20030161818A1 (en) * 2002-02-25 2003-08-28 Kansas State University Research Foundation Cultures, products and methods using stem cells
US20030166272A1 (en) * 1995-02-02 2003-09-04 Abuljadayel Ilham Saleh Method of preparing an undifferentiated cell
US6628743B1 (en) * 2002-11-26 2003-09-30 Ge Medical Systems Global Technology Company, Llc Method and apparatus for acquiring and analyzing cardiac data from a patient
US20030211602A1 (en) * 2000-04-28 2003-11-13 Anthony Atala Isolation of mesenchymal stem cells and use thereof
US20030219898A1 (en) * 2002-01-14 2003-11-27 Kiminobu Sugaya Novel mammalian multipotent stem cells and compositions, methods of preparation and methods of administration thereof
US6708055B2 (en) * 1998-08-25 2004-03-16 University Of Florida Method for automated analysis of apical four-chamber images of the heart
US20040087850A1 (en) * 2002-11-01 2004-05-06 Okerlund Darin R. Method and apparatus for medical intervention procedure planning
US20040121464A1 (en) * 2002-09-30 2004-06-24 Rathjen Peter David Method for the preparation of cells of mesodermal lineage
US20040132006A1 (en) * 2002-10-03 2004-07-08 O'donnell Thomas System and method for using delayed enhancement magnetic resonance imaging and artificial intelligence to identify non-viable myocardial tissue
US20040137612A1 (en) * 2001-04-24 2004-07-15 Dolores Baksh Progenitor cell populations , expansions thereof, and growth of non-hematopoietic cell types and tissues therefrom
US20040258669A1 (en) * 2002-11-05 2004-12-23 Dzau Victor J. Mesenchymal stem cells and methods of use thereof
US20050033143A1 (en) * 2003-05-28 2005-02-10 O'donnell Thomas Automatic optimal view determination for cardiac acquisitions
US20050054098A1 (en) * 2003-06-27 2005-03-10 Sanjay Mistry Postpartum cells derived from umbilical cord tissue, and methods of making and using the same
US20050080328A1 (en) * 2002-06-04 2005-04-14 General Electric Company Method and apparatus for medical intervention procedure planning and location and navigation of an intervention tool
US20050084959A1 (en) * 2001-10-31 2005-04-21 Hirofumi Hamada Immortalized mesenchymal cells and utilization thereof
US20050118712A1 (en) * 2003-12-02 2005-06-02 Ming-Song Tsai Two-stage culture protocol for isolating mesenchymal stem cells from amniotic fluid
US20050164380A1 (en) * 2003-11-04 2005-07-28 Trisler G. D. Stem cell culture medium and method of using said medium and the cells
US6936281B2 (en) * 2001-03-21 2005-08-30 University Of South Florida Human mesenchymal progenitor cell
US20050197568A1 (en) * 2002-03-15 2005-09-08 General Electric Company Method and system for registration of 3d images within an interventional system
US20050238215A1 (en) * 2001-10-04 2005-10-27 Marie-Pierre Jolly System and method for segmenting the left ventricle in a cardiac image
US6980682B1 (en) * 2000-11-22 2005-12-27 Ge Medical Systems Group, Llc Method and apparatus for extracting a left ventricular endocardium from MR cardiac images
US6994673B2 (en) * 2003-01-16 2006-02-07 Ge Ultrasound Israel, Ltd Method and apparatus for quantitative myocardial assessment
US20060040392A1 (en) * 2004-04-23 2006-02-23 Collins Daniel P Multi-lineage progenitor cells
US20060057657A1 (en) * 2002-03-12 2006-03-16 Oregon Health & Science University Technology & Research Collaborations Stem cell selection and differentiation
US20060073124A1 (en) * 2004-10-04 2006-04-06 Cellerix, S.L. Universidad Autonoma De Madrid Identification and isolation of multipotent cells from non-osteochondral mesenchymal tissue
US20060078993A1 (en) * 2004-08-16 2006-04-13 Cellresearch Corporation Pte Ltd Isolation, cultivation and uses of stem/progenitor cells
US20060088890A1 (en) * 2001-08-15 2006-04-27 Simmons Paul J Identification and isolation of somatic stem cells and uses thereof
US20060093586A1 (en) * 2004-10-20 2006-05-04 Vitro Diagnostics, Inc. Generation and differentiation of adult stem cell lines
US7047061B2 (en) * 2000-12-05 2006-05-16 Koninklijke Philips Electronics N.V. Method of localizing the myocardium of the heart and method of determining perfusion parameters thereof
US20060147426A1 (en) * 2003-01-30 2006-07-06 Schiller Paul C Multilineage-inducible cells and uses thereof
US20060177932A1 (en) * 2002-11-08 2006-08-10 Hiromitsu Nakauchi Expansion agents for stem cells
US20060182724A1 (en) * 2005-02-15 2006-08-17 Riordan Neil H Method for expansion of stem cells
US7113623B2 (en) * 2002-10-08 2006-09-26 The Regents Of The University Of Colorado Methods and systems for display and analysis of moving arterial tree structures
US20060223177A1 (en) * 2003-06-27 2006-10-05 Ethicon Inc. Postpartum cells derived from umbilical cord tissue, and methods of making and using the same
US20070020757A1 (en) * 2005-05-24 2007-01-25 Whitehead Institute For Biomedical Research Methods for expansion and analysis of cultured hematopoietic stem cells
US20070053885A1 (en) * 2003-05-28 2007-03-08 Shinichi Nishikawa Mesenchymal stem cell
US20070054399A1 (en) * 2003-10-29 2007-03-08 Fcb Pharmicell Co., Ltd. Method for differentiating mesenchymal stem cell into neural cell and pharmaceutical composition containing the neural cell for neurodegenerative disease
US20070072294A1 (en) * 2004-09-30 2007-03-29 Doronin Sergey V Use of human stem cells and/or factors they produce to promote adult mammalian cardiac repair through cardiomyocyte cell division
US20070077652A1 (en) * 2004-09-16 2007-04-05 Tony Peled Methods of ex vivo progenitor and stem cell expansion by co-culture with mesenchymal cells
US20070077201A1 (en) * 2004-09-29 2007-04-05 Reading Christopher L Stem cell expansion and uses
US20070077649A1 (en) * 2005-09-06 2007-04-05 Sammak Paul J Transplantable cell growth niche and related compositions and methods
US20070092967A1 (en) * 2003-11-11 2007-04-26 Hoon Han Method of isolating and culturing mesenchymal stem cell derived from umbilical cord blood
US20070098699A1 (en) * 2005-02-28 2007-05-03 Donnie Rudd Process for preparing bone marrow stem cells, and composition related thereto
US20070105221A1 (en) * 2003-11-11 2007-05-10 Hoon Han Method of isolating and culturing mesenchymal stem cell derived from cryopreserved umbilical cord blood
US20070128722A1 (en) * 2005-12-05 2007-06-07 Industrial Technology Research Institute Human mesenchymal stem cells and culturing methods thereof
US20070160583A1 (en) * 2003-08-06 2007-07-12 Claudia Lange Method for purifying mesenchymal stem cells
US20070178591A1 (en) * 2004-06-25 2007-08-02 Renomedix Institute, Inc Internally administered therapeutic agents for diseases in central and peripheral nervous system comprising mesenchymal cells as an active ingredient
US7252995B2 (en) * 2002-12-13 2007-08-07 Yu-Show Fu Method of generating neurons from stem cells and medium for culturing stem cells
US20070212336A1 (en) * 2005-10-31 2007-09-13 Fulkerson Loren D Methods for harvesting and storing autologous stem cells including blood derived hematopoietic stem cells and adipose derived mesenchymal stem cells
US20070219526A1 (en) * 2004-03-30 2007-09-20 Toby Freyman Restenosis Therapy Using Mesenchymal Stem Cells
US20070218548A1 (en) * 2004-04-26 2007-09-20 Shin-Ichi Nishikawa Mesenchymal Stem Cell Processor

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5239591A (en) 1991-07-03 1993-08-24 U.S. Philips Corp. Contour extraction in multi-phase, multi-slice cardiac mri studies by propagation of seed contours between images
US5273040A (en) 1991-11-14 1993-12-28 Picker International, Inc. Measurement of vetricle volumes with cardiac MRI
US5570430A (en) * 1994-05-31 1996-10-29 University Of Washington Method for determining the contour of an in vivo organ using multiple image frames of the organ
US7155042B1 (en) 1999-04-21 2006-12-26 Auckland Uniservices Limited Method and system of measuring characteristics of an organ
US6447453B1 (en) 2000-12-07 2002-09-10 Koninklijke Philips Electronics N.V. Analysis of cardiac performance using ultrasonic diagnostic images
GB0219408D0 (en) * 2002-08-20 2002-09-25 Mirada Solutions Ltd Computation o contour
JP2006524092A (en) 2003-04-24 2006-10-26 コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ Non-invasive left ventricular volume determination

Patent Citations (74)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5185809A (en) * 1987-08-14 1993-02-09 The General Hospital Corporation Morphometric analysis of anatomical tomographic data
US5107838A (en) * 1990-02-08 1992-04-28 Kabushiki Kaisha Toshiba Method of left ventricular volume evaluation using nuclear magnetic resonance imaging
US5195521A (en) * 1990-11-09 1993-03-23 Hewlett-Packard Company Tissue measurements
US5722405A (en) * 1993-04-15 1998-03-03 Adac Laboratories Method and apparatus for acquisition and processsing of event data in semi list mode
US5435310A (en) * 1993-06-23 1995-07-25 University Of Washington Determining cardiac wall thickness and motion by imaging and three-dimensional modeling
US5433199A (en) * 1994-02-24 1995-07-18 General Electric Company Cardiac functional analysis method using gradient image segmentation
US20030166272A1 (en) * 1995-02-02 2003-09-04 Abuljadayel Ilham Saleh Method of preparing an undifferentiated cell
US5797396A (en) * 1995-06-07 1998-08-25 University Of Florida Research Foundation Automated method for digital image quantitation
US6261549B1 (en) * 1997-07-03 2001-07-17 Osiris Therapeutics, Inc. Human mesenchymal stem cells from peripheral blood
US6387367B1 (en) * 1998-05-29 2002-05-14 Osiris Therapeutics, Inc. Human mesenchymal stem cells
US6121775A (en) * 1998-06-16 2000-09-19 Beth Israel Deaconess Medical Center, Inc. MRI imaging method and apparatus
US20020151793A1 (en) * 1998-08-25 2002-10-17 Geiser Edward A. Autonomous boundary detection system for echocardiographic images
US6708055B2 (en) * 1998-08-25 2004-03-16 University Of Florida Method for automated analysis of apical four-chamber images of the heart
US6288539B1 (en) * 1998-09-10 2001-09-11 Pheno Imaging, Inc. System for measuring an embryo, reproductive organs, and tissue in an animal
US6438403B1 (en) * 1999-11-01 2002-08-20 General Electric Company Method and apparatus for cardiac analysis using four-dimensional connectivity
US20030211602A1 (en) * 2000-04-28 2003-11-13 Anthony Atala Isolation of mesenchymal stem cells and use thereof
US6980682B1 (en) * 2000-11-22 2005-12-27 Ge Medical Systems Group, Llc Method and apparatus for extracting a left ventricular endocardium from MR cardiac images
US7047061B2 (en) * 2000-12-05 2006-05-16 Koninklijke Philips Electronics N.V. Method of localizing the myocardium of the heart and method of determining perfusion parameters thereof
US20020072674A1 (en) * 2000-12-07 2002-06-13 Criton Aline Laure Strain rate analysis in ultrasonic diagnostic images
US20020072670A1 (en) * 2000-12-07 2002-06-13 Cedric Chenal Acquisition, analysis and display of ultrasonic diagnostic cardiac images
US6537221B2 (en) * 2000-12-07 2003-03-25 Koninklijke Philips Electronics, N.V. Strain rate analysis in ultrasonic diagnostic images
US6936281B2 (en) * 2001-03-21 2005-08-30 University Of South Florida Human mesenchymal progenitor cell
US20040137612A1 (en) * 2001-04-24 2004-07-15 Dolores Baksh Progenitor cell populations , expansions thereof, and growth of non-hematopoietic cell types and tissues therefrom
US20030053667A1 (en) * 2001-05-17 2003-03-20 Nikolaos Paragios Variational approach for the segmentation of the left ventricle in MR cardiac images
US7079674B2 (en) * 2001-05-17 2006-07-18 Siemens Corporate Research, Inc. Variational approach for the segmentation of the left ventricle in MR cardiac images
US20060088890A1 (en) * 2001-08-15 2006-04-27 Simmons Paul J Identification and isolation of somatic stem cells and uses thereof
US6961454B2 (en) * 2001-10-04 2005-11-01 Siemens Corporation Research, Inc. System and method for segmenting the left ventricle in a cardiac MR image
US20050238215A1 (en) * 2001-10-04 2005-10-27 Marie-Pierre Jolly System and method for segmenting the left ventricle in a cardiac image
US20030069494A1 (en) * 2001-10-04 2003-04-10 Marie-Pierre Jolly System and method for segmenting the left ventricle in a cardiac MR image
US20050084959A1 (en) * 2001-10-31 2005-04-21 Hirofumi Hamada Immortalized mesenchymal cells and utilization thereof
US20030219898A1 (en) * 2002-01-14 2003-11-27 Kiminobu Sugaya Novel mammalian multipotent stem cells and compositions, methods of preparation and methods of administration thereof
US20030161818A1 (en) * 2002-02-25 2003-08-28 Kansas State University Research Foundation Cultures, products and methods using stem cells
US20060057657A1 (en) * 2002-03-12 2006-03-16 Oregon Health & Science University Technology & Research Collaborations Stem cell selection and differentiation
US20050197568A1 (en) * 2002-03-15 2005-09-08 General Electric Company Method and system for registration of 3d images within an interventional system
US20050080328A1 (en) * 2002-06-04 2005-04-14 General Electric Company Method and apparatus for medical intervention procedure planning and location and navigation of an intervention tool
US20040121464A1 (en) * 2002-09-30 2004-06-24 Rathjen Peter David Method for the preparation of cells of mesodermal lineage
US20040132006A1 (en) * 2002-10-03 2004-07-08 O'donnell Thomas System and method for using delayed enhancement magnetic resonance imaging and artificial intelligence to identify non-viable myocardial tissue
US7113623B2 (en) * 2002-10-08 2006-09-26 The Regents Of The University Of Colorado Methods and systems for display and analysis of moving arterial tree structures
US20040087850A1 (en) * 2002-11-01 2004-05-06 Okerlund Darin R. Method and apparatus for medical intervention procedure planning
US20040258669A1 (en) * 2002-11-05 2004-12-23 Dzau Victor J. Mesenchymal stem cells and methods of use thereof
US20060177932A1 (en) * 2002-11-08 2006-08-10 Hiromitsu Nakauchi Expansion agents for stem cells
US6628743B1 (en) * 2002-11-26 2003-09-30 Ge Medical Systems Global Technology Company, Llc Method and apparatus for acquiring and analyzing cardiac data from a patient
US7252995B2 (en) * 2002-12-13 2007-08-07 Yu-Show Fu Method of generating neurons from stem cells and medium for culturing stem cells
US6994673B2 (en) * 2003-01-16 2006-02-07 Ge Ultrasound Israel, Ltd Method and apparatus for quantitative myocardial assessment
US20060147426A1 (en) * 2003-01-30 2006-07-06 Schiller Paul C Multilineage-inducible cells and uses thereof
US20050033143A1 (en) * 2003-05-28 2005-02-10 O'donnell Thomas Automatic optimal view determination for cardiac acquisitions
US20070053885A1 (en) * 2003-05-28 2007-03-08 Shinichi Nishikawa Mesenchymal stem cell
US20050054098A1 (en) * 2003-06-27 2005-03-10 Sanjay Mistry Postpartum cells derived from umbilical cord tissue, and methods of making and using the same
US20050058631A1 (en) * 2003-06-27 2005-03-17 Kihm Anthony J. Postpartum cells derived from placental tissue, and methods of making and using the same
US20070014771A1 (en) * 2003-06-27 2007-01-18 Ethicon, Incorporated Postpartum cells derived from umbilical cord tissue, and methods of making and using the same
US20060223177A1 (en) * 2003-06-27 2006-10-05 Ethicon Inc. Postpartum cells derived from umbilical cord tissue, and methods of making and using the same
US20070160583A1 (en) * 2003-08-06 2007-07-12 Claudia Lange Method for purifying mesenchymal stem cells
US20070054399A1 (en) * 2003-10-29 2007-03-08 Fcb Pharmicell Co., Ltd. Method for differentiating mesenchymal stem cell into neural cell and pharmaceutical composition containing the neural cell for neurodegenerative disease
US20050164380A1 (en) * 2003-11-04 2005-07-28 Trisler G. D. Stem cell culture medium and method of using said medium and the cells
US20070092967A1 (en) * 2003-11-11 2007-04-26 Hoon Han Method of isolating and culturing mesenchymal stem cell derived from umbilical cord blood
US20070105221A1 (en) * 2003-11-11 2007-05-10 Hoon Han Method of isolating and culturing mesenchymal stem cell derived from cryopreserved umbilical cord blood
US7101710B2 (en) * 2003-12-02 2006-09-05 Ming-Song Tsai Two-stage culture protocol for isolating mesenchymal stem cells from amniotic fluid
US20050118712A1 (en) * 2003-12-02 2005-06-02 Ming-Song Tsai Two-stage culture protocol for isolating mesenchymal stem cells from amniotic fluid
US20070219526A1 (en) * 2004-03-30 2007-09-20 Toby Freyman Restenosis Therapy Using Mesenchymal Stem Cells
US20060040392A1 (en) * 2004-04-23 2006-02-23 Collins Daniel P Multi-lineage progenitor cells
US20070218548A1 (en) * 2004-04-26 2007-09-20 Shin-Ichi Nishikawa Mesenchymal Stem Cell Processor
US20070178591A1 (en) * 2004-06-25 2007-08-02 Renomedix Institute, Inc Internally administered therapeutic agents for diseases in central and peripheral nervous system comprising mesenchymal cells as an active ingredient
US20060078993A1 (en) * 2004-08-16 2006-04-13 Cellresearch Corporation Pte Ltd Isolation, cultivation and uses of stem/progenitor cells
US20070077652A1 (en) * 2004-09-16 2007-04-05 Tony Peled Methods of ex vivo progenitor and stem cell expansion by co-culture with mesenchymal cells
US20070077201A1 (en) * 2004-09-29 2007-04-05 Reading Christopher L Stem cell expansion and uses
US20070072294A1 (en) * 2004-09-30 2007-03-29 Doronin Sergey V Use of human stem cells and/or factors they produce to promote adult mammalian cardiac repair through cardiomyocyte cell division
US20060073124A1 (en) * 2004-10-04 2006-04-06 Cellerix, S.L. Universidad Autonoma De Madrid Identification and isolation of multipotent cells from non-osteochondral mesenchymal tissue
US20060093586A1 (en) * 2004-10-20 2006-05-04 Vitro Diagnostics, Inc. Generation and differentiation of adult stem cell lines
US20060182724A1 (en) * 2005-02-15 2006-08-17 Riordan Neil H Method for expansion of stem cells
US20070098699A1 (en) * 2005-02-28 2007-05-03 Donnie Rudd Process for preparing bone marrow stem cells, and composition related thereto
US20070020757A1 (en) * 2005-05-24 2007-01-25 Whitehead Institute For Biomedical Research Methods for expansion and analysis of cultured hematopoietic stem cells
US20070077649A1 (en) * 2005-09-06 2007-04-05 Sammak Paul J Transplantable cell growth niche and related compositions and methods
US20070212336A1 (en) * 2005-10-31 2007-09-13 Fulkerson Loren D Methods for harvesting and storing autologous stem cells including blood derived hematopoietic stem cells and adipose derived mesenchymal stem cells
US20070128722A1 (en) * 2005-12-05 2007-06-07 Industrial Technology Research Institute Human mesenchymal stem cells and culturing methods thereof

Cited By (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7864997B2 (en) * 2006-04-28 2011-01-04 Pie Medical Imaging B.V. Method, apparatus and computer program product for automatic segmenting of cardiac chambers
US20070253609A1 (en) * 2006-04-28 2007-11-01 Aben Jean-Paul M M Method, Apparatus and Computer Program Product for Automatic Segmenting of Cardiac Chambers
US20090149734A1 (en) * 2007-12-07 2009-06-11 Kabushiki Kaisha Toshiba Diagnostic imaging apparatus, magnetic resonance imaging apparatus, and x-ray ct apparatus
US8909321B2 (en) * 2007-12-07 2014-12-09 Kabushiki Kaisha Toshiba Diagnostic imaging apparatus, magnetic resonance imaging apparatus, and X-ray CT apparatus
US20100303328A1 (en) * 2008-01-31 2010-12-02 Koninklijke Philips Electronics N.V. Automatic 3-d segmentation of the short-axis late-enhancement cardiac mri
US8509506B2 (en) 2008-01-31 2013-08-13 Koninklijke Philips N.V. Automatic 3-D segmentation of the short-axis late-enhancement cardiac MRI
US8981770B2 (en) * 2009-07-20 2015-03-17 Koninklijke Philips N.V. Apparatus and method for influencing and/or detecting magnetic particles
US20120146632A1 (en) * 2009-07-20 2012-06-14 Koninklijke Philips Electronics N.V. Apparatus and method for influencing and/or detecting magnetic particles
WO2011107528A1 (en) 2010-03-04 2011-09-09 Europejskie Centrum Zdrowia Otwock Sp. Z O.O. A device and a method for imaging the left ventricle of a heart
EP2372639A1 (en) 2010-03-04 2011-10-05 Europejskie Centrum Zdrowia Otwock Sp. z o.o. A device and a method for imaging the left ventricle of a heart
US10495713B2 (en) 2011-07-07 2019-12-03 The Board Of Trustees Of The Leland Stanford Junior University Comprehensive cardiovascular analysis with volumetric phase-contrast MRI
US20150023577A1 (en) * 2012-03-05 2015-01-22 Hong'en (Hangzhou, China) Medical Technology Inc. Device and method for determining physiological parameters based on 3d medical images
US20140005526A1 (en) * 2012-07-02 2014-01-02 Assaf Govari Catheter with synthetic aperture mri sensor
US10398344B2 (en) 2014-01-17 2019-09-03 Arterys Inc. Apparatus, methods and articles for four dimensional (4D) flow magnetic resonance imaging
US11515032B2 (en) 2014-01-17 2022-11-29 Arterys Inc. Medical imaging and efficient sharing of medical imaging information
US10871536B2 (en) 2015-11-29 2020-12-22 Arterys Inc. Automated cardiac volume segmentation
WO2018140596A3 (en) * 2017-01-27 2018-09-07 Arterys Inc. Automated segmentation utilizing fully convolutional networks
US10600184B2 (en) 2017-01-27 2020-03-24 Arterys Inc. Automated segmentation utilizing fully convolutional networks
US10902598B2 (en) 2017-01-27 2021-01-26 Arterys Inc. Automated segmentation utilizing fully convolutional networks
US11551353B2 (en) 2017-11-22 2023-01-10 Arterys Inc. Content based image retrieval for lesion analysis

Also Published As

Publication number Publication date
WO2004097720A1 (en) 2004-11-11
ATE470199T1 (en) 2010-06-15
EP1620827B1 (en) 2010-06-02
EP1620827A1 (en) 2006-02-01
DE602004027479D1 (en) 2010-07-15
CN1777898A (en) 2006-05-24
CN100377165C (en) 2008-03-26
US7603154B2 (en) 2009-10-13
JP2006524092A (en) 2006-10-26
WO2004097720A8 (en) 2005-03-31

Similar Documents

Publication Publication Date Title
US7603154B2 (en) Non-invasive left ventricular volume determination
Nesser et al. Volumetric analysis of regional left ventricular function with real-time three-dimensional echocardiography: validation by magnetic resonance and clinical utility testing
US9924869B2 (en) Method and apparatus for determining blood flow required, method and apparatus for producing blood flow image, and method and apparatus for processing myocardial perfusion image
Goshtasby et al. Segmentation of cardiac cine MR images for extraction of right and left ventricular chambers
Chang et al. Feasibility of single-beat full-volume capture real-time three-dimensional echocardiography and auto-contouring algorithm for quantification of left ventricular volume: validation with cardiac magnetic resonance imaging
US8315447B2 (en) Method for processing medical image data and magnetic resonance apparatus for recording and processing medical image data
Varga-Szemes et al. Clinical feasibility of a myocardial signal intensity threshold-based semi-automated cardiac magnetic resonance segmentation method
US8487933B2 (en) System and method for multi-segment center point trajectory mapping
US20100245360A1 (en) System and method for center point trajectory mapping
Corsi et al. Quantification of regional left ventricular wall motion from real-time 3-dimensional echocardiography in patients with poor acoustic windows: effects of contrast enhancement tested against cardiac magnetic resonance
JP7278056B2 (en) Improved left ventricular segmentation in contrast-enhanced cine MRI datasets
Compas et al. Radial basis functions for combining shape and speckle tracking in 4D echocardiography
Veronesi et al. Tracking of left ventricular long axis from real-time three-dimensional echocardiography using optical flow techniques
FLEAGLE et al. Automated identification of left ventricular borders from spin-echo magnetic resonance images: experimental and clinical feasibility studies
US10776998B1 (en) Method and system for analysis of 3D deformations and regional function of a heart with 3D SinMod
Caiani et al. Dual triggering improves the accuracy of left ventricular volume measurements by contrast-enhanced real-time 3-dimensional echocardiography
US20120008833A1 (en) System and method for center curve displacement mapping
Mazonakis et al. Development and evaluation of a semiautomatic segmentation method for the estimation of LV parameters on cine MR images
Najman et al. An open, clinically-validated database of 3D+ t cine-MR images of the left ventricle with associated manual and automated segmentations
EP3613013B1 (en) System and method for medical imaging
Wesarg et al. An automated 4D approach for left ventricular assessment in clinical cine MR images
Pednekar et al. Automatic computation of left ventricular ejection fraction from spatiotemporal information in cine‐SSFP cardiac MR images
Zhong et al. Regional assessment of left ventricular surface shape from magnetic resonance imaging
Palma et al. Cardiac Magnetic Resonance protocol and patient preparation
Maceira et al. Global and regional cardiac function

Legal Events

Date Code Title Description
AS Assignment

Owner name: KONINKLIJKE PHILIPS ELECTRONICS, N.V., NETHERLANDS

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:NOBLE, NICHOLAS MICHAEL IAN;BREEUWER, MARCEL;REEL/FRAME:017886/0851;SIGNING DATES FROM 20050414 TO 20050421

STCF Information on status: patent grant

Free format text: PATENTED CASE

FPAY Fee payment

Year of fee payment: 4

FPAY Fee payment

Year of fee payment: 8

MAFP Maintenance fee payment

Free format text: PAYMENT OF MAINTENANCE FEE, 12TH YEAR, LARGE ENTITY (ORIGINAL EVENT CODE: M1553); ENTITY STATUS OF PATENT OWNER: LARGE ENTITY

Year of fee payment: 12